{"as_of":"2026-08-07T15:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:84872510fd7c6cdc7c7220750d7ad824db9c088da384bb76c0a9f1f86a1eabef","coverage":[{"denominator":59,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":59,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:32:22.248034Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-21T03:56:29.983335Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-21T03:59:32.488072Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"cited_work":{"arxiv_id":"2506.07759","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.07759","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2506.07759 (2025)","venue":null,"work_id":"da488246-6e2f-4725-8966-24ed3eaab049","year":2025},"citing_paper":{"arxiv_id":"2605.20849","last_updated":"2026-05-20T07:40:05Z","snapshot_observed_at":"2026-08-05T14:32:21.145968Z","submitted_at":"2026-05-20T07:40:05Z","title":"Large Language Models for Operations Research: A Comprehensive Survey","version":1},"reference_index":118,"source":"pdf_text","source_observed_at":"2026-05-21T03:56:29.983335Z"},"links":{"cited_paper":"/paper/2506.07759","citing_paper":"/paper/2605.20849"},"observation_digest":"sha256:310fc1aa79724c88ab0314bae319e0f5796c6cc97d35a6946fd7c7b08d54b9f8","observation_id":"5793778b-efa1-4b4f-b69a-19620e48cca3","resolution":{"observed_at":"2026-05-21T03:59:32.489378Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.07759/citation-record","integrity":"/paper/2506.07759/integrity","json":"/paper/2506.07759/citation-record.json","paper":"/paper/2506.07759"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:23.146530Z","title":"When large language model meets optimization,","venue":null,"work_id":"6b80c34c-e388-4ef2-8777-6beb56613f66","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.073130Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:8197ec7621c7e7037268e07b5835230c9fdd88637747588a114f2b0133b9a625","observation_id":"1ee5571d-3275-410f-9e58-ea52ac19137c","resolution":{"observed_at":"2026-08-07T05:32:23.149656Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:23.137289Z","title":"Particle swarm optimization algorithm and its applications: a systematic review,","venue":null,"work_id":"1e3aadaa-2848-4835-9eff-f582875fc7cd","year":2022},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.076698Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:675377c851cb33cf5cfa7ed45bcc2054307b9ca3cc1427051692f8aa37a53df7","observation_id":"3da7b673-1af4-4f60-9d41-a435d66cd4d6","resolution":{"observed_at":"2026-08-07T05:32:23.140428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:23.127876Z","title":"A review on representative swarm intelligence algorithms for solving optimization problems: Applications and trends,","venue":null,"work_id":"1f67c73f-3cf9-4df3-baee-bff060eb4c2b","year":2021},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.080122Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:f0c2cf13abfbe495fc0e79cb850e3c784648476ce520efe524e6c763482af27c","observation_id":"563ea063-26fe-48b7-9eda-d07db7e4acd7","resolution":{"observed_at":"2026-08-07T05:32:23.130965Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:23.118169Z","title":"A blockchain-based llm-driven energy-efficient scheduling system towards distributed multi-agent manufacturing scenario of new energy ve- hicles within the circular economy,","venue":null,"work_id":"878127be-915e-44ae-aa75-41850ff07f52","year":2025},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.083561Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:b619c8fc45f57ba114ee40f1d63fb18514e345d68a55856a32177db5f6b6a69f","observation_id":"83eddcbb-5406-44e7-bee3-ecd1ef90938c","resolution":{"observed_at":"2026-08-07T05:32:23.121814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:23.013478Z","title":"An llm-based approach for enabling seamless human-robot collaboration in assembly,","venue":null,"work_id":"8dee1566-0590-4648-bfa8-d8167d2d541c","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.086665Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:b020f17324572652df0d2d76b1b9c47d0bf004d0d960f0b68a4ed78aba9fa669","observation_id":"542a22dc-b3b4-4c62-8a10-5c191d41749c","resolution":{"observed_at":"2026-08-07T05:32:23.111403Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10034","last_updated":"2024-05-29T09:00:25Z","snapshot_observed_at":"2026-08-04T00:24:49.443617Z","submitted_at":"2024-01-18T14:58:17Z","title":"Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.10034","snapshot_observed_at":"2026-08-07T05:32:22.090196Z","title":"Evolutionary computation in the era of large language model: Survey and roadmap,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.090196Z"},"links":{"cited_paper":"/paper/2401.10034","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:a20ef7bdd214fa1d4b20ab5b8b4799a6fe4dda4688aa6725fb7b1e5c73cb0e23","observation_id":"72081117-5a0e-4f00-8054-ec5e9fa2ef0a","resolution":{"observed_at":"2026-08-07T05:32:22.090196Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"3133.35964","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.555591Z","title":"Leveraging large language models for the generation of novel metaheuristic optimization algorithms,","venue":null,"work_id":"858ebf4c-919a-49b8-ac83-a3fc6dc2f4d4","year":2023},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.094080Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:2cac521e94291dd6301c4d44397ea0c0bab6e49fe0c12cc2506dbb84f08f1f39","observation_id":"54de55f6-5fc9-4b5f-9a7c-18725acbff91","resolution":{"observed_at":"2026-08-07T05:32:22.561103Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:23.003688Z","title":"Llmoa: A novel large language model assisted hyper- heuristic optimization algorithm,","venue":null,"work_id":"8eb707cb-acb0-4f6d-98df-bbd5b06f0b51","year":2025},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.097320Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:01e0762368caab37cfe9452e7a56ff877438aba14a5ab97e1e4033adee079b50","observation_id":"b930eba4-d839-44a5-a69a-fb2cafb23f99","resolution":{"observed_at":"2026-08-07T05:32:23.006848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02051","last_updated":"2024-06-01T16:48:37Z","snapshot_observed_at":"2026-08-06T00:20:28.197923Z","submitted_at":"2024-01-04T04:11:59Z","title":"Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02051","snapshot_observed_at":"2026-08-07T05:32:22.100148Z","title":"Evolution of heuristics: Towards efficient automatic algorithm design using large language model,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.100148Z"},"links":{"cited_paper":"/paper/2401.02051","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:034611e9eb0e879d409c85d2329376f01217f1971d1e22d9687999b3b596351d","observation_id":"2ce2e4f7-f9ff-48e9-9024-a7e4abfd309f","resolution":{"observed_at":"2026-08-07T05:32:22.100148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.993576Z","title":"Chen and Y","venue":null,"work_id":"4b25fcb5-40a9-40ca-9939-869908b04ea9","year":2025},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.103603Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:bf446cd814dc0aef064f5952e3f9a75116e32433e7cf3389cb722d7bb5dff82a","observation_id":"f9b7e67d-001c-4729-ae94-e9c1681367f3","resolution":{"observed_at":"2026-08-07T05:32:22.996936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.19839","last_updated":"2024-03-28T21:20:27Z","snapshot_observed_at":"2026-07-06T17:52:50.835744Z","submitted_at":"2024-03-28T21:20:27Z","title":"The New Agronomists: Language Models are Experts in Crop Management","version":1},"cited_work":{"arxiv_id":"2403.19839","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.19839","snapshot_observed_at":"2026-08-07T05:32:22.480731Z","title":"The New Agronomists: Language Models are Experts in Crop Management","venue":"cs.LG","work_id":"1cf350af-5911-417a-9662-7d85df2f2677","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.106887Z"},"links":{"cited_paper":"/paper/2403.19839","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:32634e86d2770f6c779c06168f5c15d6ff184754daede551307eb70389142433","observation_id":"c060bab3-f1d3-46ef-af7e-9db5b65c283b","resolution":{"observed_at":"2026-08-07T05:32:22.484168Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.982838Z","title":"Automl-gpt: Automatic machine learning with gpt,","venue":null,"work_id":"7772b65d-42a4-4421-8307-8c19452e9124","year":null},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.109962Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:4851b483ea528e7bc99451f6a73f3367ca1e815c80f9396f028854578a446536","observation_id":"4cd8d749-c664-474c-8371-3691e066e769","resolution":{"observed_at":"2026-08-07T05:32:22.986294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04528","last_updated":"2024-11-11T17:30:55Z","snapshot_observed_at":"2026-07-06T16:58:27.612525Z","submitted_at":"2023-12-07T18:46:50Z","title":"Using Large Language Models for Hyperparameter Optimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04528","snapshot_observed_at":"2026-08-07T05:32:22.116084Z","title":"Using large language models for hyperparameter optimization,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.116084Z"},"links":{"cited_paper":"/paper/2312.04528","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:606ff3a994816aa7173208a22c0f7f4b54af156e1296eb3aa86dde87763b58e1","observation_id":"694ab944-28d8-43ea-8d05-20d2fc348644","resolution":{"observed_at":"2026-08-07T05:32:22.116084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01881","last_updated":"2025-02-26T13:57:13Z","snapshot_observed_at":"2026-07-06T17:24:37.090243Z","submitted_at":"2024-02-02T20:12:05Z","title":"Large Language Model Agent for Hyper-Parameter Optimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01881","snapshot_observed_at":"2026-08-07T05:32:22.119463Z","title":"Large language model agent for hyper-parameter optimization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.119463Z"},"links":{"cited_paper":"/paper/2402.01881","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:6080fd5d0f976f80dce12a46d1f608800181fa6dcd5197f7850103b1f8102e51","observation_id":"14825a8e-91f7-4913-91a2-f943fc461368","resolution":{"observed_at":"2026-08-07T05:32:22.119463Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.903759Z","title":"Understanding llms: A comprehensive overview from training to inference,","venue":null,"work_id":"32391e9d-738c-4b82-8c40-63efe2fc0732","year":2025},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.122581Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:63f239f3dcf6b69ffdab2f6bab59f431be9f5b2351af07d083213f84aa2acddb","observation_id":"5f761ec0-5f53-42b2-95b5-5b3b95bd1550","resolution":{"observed_at":"2026-08-07T05:32:22.924730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16797","last_updated":"2023-09-28T19:01:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-28T19:01:07Z","title":"Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16797","snapshot_observed_at":"2026-08-07T05:32:22.125343Z","title":"Promptbreeder: Self-referential self-improvement via prompt evolution,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.125343Z"},"links":{"cited_paper":"/paper/2309.16797","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:98052116c1f50a6a03656990a166140e7a422724528bf3e5d291149afaa07335","observation_id":"96e4c839-f7ea-41ad-abb7-2901e4a75775","resolution":{"observed_at":"2026-08-07T05:32:22.125343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.03409","last_updated":"2024-04-15T07:50:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-07T00:07:15Z","title":"Large Language Models as Optimizers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.03409","snapshot_observed_at":"2026-08-07T05:32:22.128468Z","title":"Large language models as optimizers,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.128468Z"},"links":{"cited_paper":"/paper/2309.03409","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:02627e0e0b359301f6b4a2c8fddf9e7ebf7397a9bfad90bd96775054998a62f4","observation_id":"5f087f9c-0be2-4f3c-b344-2fb5a884370e","resolution":{"observed_at":"2026-08-07T05:32:22.128468Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06116","last_updated":"2023-10-30T18:23:45Z","snapshot_observed_at":"2026-07-06T16:30:08.320348Z","submitted_at":"2023-10-09T19:47:03Z","title":"OptiMUS: Optimization Modeling Using MIP Solvers and large language models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06116","snapshot_observed_at":"2026-08-07T05:32:22.131377Z","title":"Optimus: Optimization modeling using mip solvers and large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.131377Z"},"links":{"cited_paper":"/paper/2310.06116","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:91eb1ed2417e72c763dfe9c707967502e4af63773ff3d5c9c5144912a3c86b70","observation_id":"265df7b6-0d1f-4534-915e-8f540c1dbb1d","resolution":{"observed_at":"2026-08-07T05:32:22.131377Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02905","last_updated":"2024-06-23T23:59:53Z","snapshot_observed_at":"2026-07-06T16:27:43.345022Z","submitted_at":"2023-10-02T02:01:16Z","title":"Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02905","snapshot_observed_at":"2026-08-07T05:32:22.134597Z","title":"Use your instinct: Instruction optimization for llms using neural bandits coupled with transformers,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.134597Z"},"links":{"cited_paper":"/paper/2310.02905","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:95d92cca2b760459b654bc829c729a4396f565bbff01bd66185b6aa4663e9d53","observation_id":"415c7523-7eb4-42a5-8cd7-2240fe2988b8","resolution":{"observed_at":"2026-08-07T05:32:22.134597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.857064Z","title":"Leveraging PRE-PRINT SUBMITTED TO IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 20 large language model to generate a novel metaheuristic algorithm with CRISPE framework,","venue":null,"work_id":"862cf300-57b0-45ed-abf5-84f24debd810","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.137379Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:f98da55124bd6c60c0e2c6ac44320df61bfe1a5034d0f0c91b9c6e1c1d8569b2","observation_id":"ef0fa2a8-2598-48a3-89e8-35afc6356e1f","resolution":{"observed_at":"2026-08-07T05:32:22.876158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.140102Z","title":"Evolutionary computation in the era of large language model: Survey and roadmap,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.140102Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:40ff6c6e490c5434c8659e2b0b9b6ac18981217ec4a444e4af3885f8a7e4c192","observation_id":"5c491cfd-f700-426a-9584-8b2e8010d513","resolution":{"observed_at":"2026-08-07T05:32:22.140102Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15249","last_updated":"2023-11-26T09:38:44Z","snapshot_observed_at":"2026-07-06T16:52:27.457437Z","submitted_at":"2023-11-26T09:38:44Z","title":"Algorithm Evolution Using Large Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15249","snapshot_observed_at":"2026-08-07T05:32:22.142891Z","title":"Algorithm evolution using large language model,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.142891Z"},"links":{"cited_paper":"/paper/2311.15249","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:c01aaad3f6ccc66d935ab5350cd78337d82dcb7a818fd71c8fbea3c6033ea402","observation_id":"c14bdb64-ff9a-46c6-84f0-67382e1341d2","resolution":{"observed_at":"2026-08-07T05:32:22.142891Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.775603Z","title":"Llamea: A large language model evolutionary algorithm for automatically generat- ing metaheuristics,","venue":null,"work_id":"d5fe97d6-4558-4de0-a8af-dc12038a3930","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.145766Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:b2f343654138b16e364097ae28fc3ff6874262e165eae2e88aa9f65adf337d61","observation_id":"78446301-90c8-4ea2-8e37-24c2825c50eb","resolution":{"observed_at":"2026-08-07T05:32:22.803491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.07102","last_updated":"2024-01-13T15:57:54Z","snapshot_observed_at":"2026-07-06T17:15:10.548959Z","submitted_at":"2024-01-13T15:57:54Z","title":"Evolving Code with A Large Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.07102","snapshot_observed_at":"2026-08-07T05:32:22.148582Z","title":"Evolving code with a large language model,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.148582Z"},"links":{"cited_paper":"/paper/2401.07102","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:2085cbd62b086b1db5321f490188e0bd094c1aab734ee39e419c922a080844fb","observation_id":"83df3fa2-91c9-488b-812d-9e56abb8f4de","resolution":{"observed_at":"2026-08-07T05:32:22.148582Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10802","last_updated":"2025-07-25T06:26:07Z","snapshot_observed_at":"2026-08-04T06:27:19.314059Z","submitted_at":"2025-02-15T13:52:30Z","title":"CoCoEvo: Co-Evolution of Programs and Test Cases to Enhance Code Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.10802","snapshot_observed_at":"2026-08-07T05:32:22.151646Z","title":"Cocoevo: Co-evolution of programs and test cases to enhance code generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.151646Z"},"links":{"cited_paper":"/paper/2502.10802","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:87db88cf5c2159ebfcbf9dcfe3f1e438566cb010b869b1f99fff16559400718a","observation_id":"e794f491-f068-42f9-9884-26e9334e98ab","resolution":{"observed_at":"2026-08-07T05:32:22.151646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.02054","last_updated":"2024-03-04T13:57:37Z","snapshot_observed_at":"2026-08-05T09:23:51.152040Z","submitted_at":"2024-03-04T13:57:37Z","title":"Large Language Model-Based Evolutionary Optimizer: Reasoning with elitism","version":1},"cited_work":{"arxiv_id":"2403.02054","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.02054","snapshot_observed_at":"2026-08-07T05:32:22.382493Z","title":"Large Language Model-Based Evolutionary Optimizer: Reasoning with elitism","venue":"cs.AI","work_id":"5a282736-b0e9-4f7d-a91a-b7b923a140d7","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.154868Z"},"links":{"cited_paper":"/paper/2403.02054","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:2f77f0acf18f2622e591d6661994cc6e478973ac312e2f7f885b0c448cd2fe0e","observation_id":"2a775846-95a1-4144-9188-e55f43e4eadc","resolution":{"observed_at":"2026-08-07T05:32:22.385886Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.19046","last_updated":"2024-04-26T06:24:59Z","snapshot_observed_at":"2026-08-02T19:01:58.611954Z","submitted_at":"2023-10-29T15:44:52Z","title":"Large Language Models as Evolutionary Optimizers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.19046","snapshot_observed_at":"2026-08-07T05:32:22.157861Z","title":"Large language models as evolutionary optimizers,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.157861Z"},"links":{"cited_paper":"/paper/2310.19046","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:047e1646a7e5faa18f568e81eb7549d0f8986507a175258d92ef93baac50b14a","observation_id":"57771152-9693-43bf-ae43-bfad4628c996","resolution":{"observed_at":"2026-08-07T05:32:22.157861Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.763825Z","title":"Quality-diversity through ai feedback,","venue":null,"work_id":"8adae083-bdc3-488d-844d-9058ed097912","year":null},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.160883Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:b51c79ca8cf8285ba78f96cc9382b085fb5870b08e34a9d8c31ff51585509b77","observation_id":"034deb52-1be1-499c-ae36-97df6ffeb5a9","resolution":{"observed_at":"2026-08-07T05:32:22.767440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.744941Z","title":"Language model crossover: Variation through few-shot prompting,","venue":null,"work_id":"8c4a070f-5a4a-44fa-9745-aa9ef064d57a","year":null},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.166998Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:8a6967e19e6c2547126853d7d1f0d77b341e328588ae938c934ed957f12fbb63","observation_id":"b9d05c14-ca3a-46f9-ab97-6ef530efe057","resolution":{"observed_at":"2026-08-07T05:32:22.748182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.753908Z","title":"Available: https://arxiv.org/abs/2310","venue":null,"work_id":"d789053d-b59c-487a-9af2-d00a7ee59a86","year":null},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.163971Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:36ece92315b5d295796e0f59a6d0ea118db745f991a5c2c7e79dccde23fcd0f7","observation_id":"2a834729-35cb-4900-8271-4058695b31c5","resolution":{"observed_at":"2026-08-07T05:32:22.757239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12541","last_updated":"2024-03-26T12:04:44Z","snapshot_observed_at":"2026-07-06T16:35:27.763870Z","submitted_at":"2023-10-19T07:46:54Z","title":"Large Language Model for Multi-objective Evolutionary Optimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12541","snapshot_observed_at":"2026-08-07T05:32:22.176624Z","title":"Large language model for multi-objective evolutionary optimization,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.176624Z"},"links":{"cited_paper":"/paper/2310.12541","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:5c200164f8034a4ede8d0903fac4150e058bf31e2c0e98a94caf82d28bc1971a","observation_id":"a221f0dc-5675-453d-947a-384a251f7e30","resolution":{"observed_at":"2026-08-07T05:32:22.176624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22657","last_updated":"2024-10-30T02:54:31Z","snapshot_observed_at":"2026-07-06T19:41:59.246720Z","submitted_at":"2024-10-30T02:54:31Z","title":"Automatic programming via large language models with population self-evolution for dynamic job shop scheduling problem","version":1},"cited_work":{"arxiv_id":"2410.22657","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.22657","snapshot_observed_at":"2026-08-07T05:32:22.347605Z","title":"Automatic programming via large language models with population self-evolution for dynamic job shop scheduling problem","venue":"cs.NE","work_id":"dda59c7c-3a92-4927-bb9c-9d3062fb99ea","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.179996Z"},"links":{"cited_paper":"/paper/2410.22657","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:c2f097d486a99f76a006c6d1314a0cdc9110a4f02dbd47a73bb9a461791a2797","observation_id":"ff9cc0ce-61da-4bdd-ab42-803600ad52a6","resolution":{"observed_at":"2026-08-07T05:32:22.352389Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.173802Z","title":"Bradley, H","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.173802Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:570f5a8b692f19d675fd09a91d5ed3d6b9bdf0aac180f3e87566a5862128818c","observation_id":"35498366-5179-4c63-bd33-a7f527d5c107","resolution":{"observed_at":"2026-08-07T05:32:22.173802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01145","last_updated":"2024-10-14T13:50:46Z","snapshot_observed_at":"2026-08-05T23:20:20.445925Z","submitted_at":"2024-02-02T05:04:51Z","title":"ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01145","snapshot_observed_at":"2026-08-07T05:32:22.186136Z","title":"Reevo: Large language models as hyper-heuristics with reflective evolution,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.186136Z"},"links":{"cited_paper":"/paper/2402.01145","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:2b9629d0d4ffc3ec31a7e1425a895978f3819b1b9f5f0e2e18bed9a8840d2f24","observation_id":"8a5f8134-6b87-4e43-94f8-264a54c08265","resolution":{"observed_at":"2026-08-07T05:32:22.186136Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14995","last_updated":"2024-12-19T16:07:00Z","snapshot_observed_at":"2026-08-06T16:02:22.309330Z","submitted_at":"2024-12-19T16:07:00Z","title":"HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14995","snapshot_observed_at":"2026-08-07T05:32:22.189152Z","title":"Hsevo: Elevating automatic heuristic design with diversity-driven harmony search and genetic algorithm using llms,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.189152Z"},"links":{"cited_paper":"/paper/2412.14995","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:c0def18fa224fd8ccc13b249e194142166b2109d1b281748a16b562cc0caa8df","observation_id":"c2a0717c-aaa3-4940-9d9f-20e71d09ad5e","resolution":{"observed_at":"2026-08-07T05:32:22.189152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09063","last_updated":"2024-09-04T10:00:32Z","snapshot_observed_at":"2026-07-06T19:15:08.847236Z","submitted_at":"2024-09-04T10:00:32Z","title":"TS-EoH: An Edge Server Task Scheduling Algorithm Based on Evolution of Heuristic","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09063","snapshot_observed_at":"2026-08-07T05:32:22.183084Z","title":"Ts-eoh: An edge server task scheduling algorithm based on evolution of heuristic,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.183084Z"},"links":{"cited_paper":"/paper/2409.09063","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:a6fa3e888d5ea1fe8ba467c9ac83e749de8efba806a83a64f79d5d41991de0b6","observation_id":"f5bc6231-5678-47aa-89c9-bfb91e776e1f","resolution":{"observed_at":"2026-08-07T05:32:22.183084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.727479Z","title":"A survey of job shop scheduling problem: The types and models,","venue":null,"work_id":"633e11bd-228e-4a52-aec2-ac80626684a8","year":2022},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.195278Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:5978db11ecda4df54e417e43261a1291f156deeecfaa0b5b158a913b0d40165e","observation_id":"69d5d99f-d680-452d-9a12-247905ba3284","resolution":{"observed_at":"2026-08-07T05:32:22.730408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.718671Z","title":"The flexible job shop scheduling problem: A review,","venue":null,"work_id":"12244147-1444-45f2-bb38-5ebab0ff8575","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.197886Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:0d58fee363068bed6a2eaf7f7826117a2e854488fdb212792647f0ce204607f9","observation_id":"495b0acb-891a-4869-8411-524d79fda0cc","resolution":{"observed_at":"2026-08-07T05:32:22.721756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-030-33820-6_9","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.280769Z","title":"Gavval and V","venue":null,"work_id":"bc89b66b-e50b-4999-9d08-b1318ad20325","year":2020},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.192427Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:36cb2e61fd2a33ff09ae0db76154b87f6f77e0ebeabbcf269e48b8e4fa37bc13","observation_id":"4f308e84-9874-4474-9166-9a0ec56f537a","resolution":{"observed_at":"2026-08-07T05:32:22.284640Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.701325Z","title":"Solving the job-shop schedul- ing problem in the industry 4.0 era,","venue":null,"work_id":"2490547a-9eea-418b-85eb-8895073b77b3","year":2018},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.203843Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:eba83650b95bd53aaf83f95f65bf59d5f85b885bbdfa1c5a3f3f8eedc6a817c8","observation_id":"19ebf896-678e-4b92-8ddd-5de12ae335e0","resolution":{"observed_at":"2026-08-07T05:32:22.704432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.206560Z","title":"Routing and scheduling in a flexible job shop by tabu search,","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.206560Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:187773388247216e4e3eb649c9832a6e9f3607d66840421bb4fb098256d0871c","observation_id":"fe5a610d-1063-4c7d-baf7-e6ee9a7333ee","resolution":{"observed_at":"2026-08-07T05:32:22.206560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.710066Z","title":"Review on flexible job shop scheduling,","venue":null,"work_id":"025158ec-fbf8-48cc-a84a-51a9f5bffe8e","year":2019},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.200590Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:77dddd1a6e5db58260544459ddb8935af827fef78b18082fa212f5307c177a82","observation_id":"c703728b-f421-4d72-ab9d-39c065f80b65","resolution":{"observed_at":"2026-08-07T05:32:22.713086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.683813Z","title":"Ibm ilog cp optimizer for detailed schedul- ing illustrated on three problems,","venue":null,"work_id":"082bac1d-7a66-4c81-b57f-7509d48bfa1e","year":2009},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.212092Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:a7cda7ab666398f57d53dd3f521f06470f63489592263c41c4b82b348675fe4d","observation_id":"8818ca36-a153-478c-9f5b-5ee8c453eb5f","resolution":{"observed_at":"2026-08-07T05:32:22.687119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.674873Z","title":"Industrial size job shop scheduling tackled by present day cp solvers,","venue":null,"work_id":"871dab41-c7f2-4935-ace1-53449bfe0ad0","year":2019},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.214872Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:c5e9aefd2faff9fc6a755b7e0f2a36558af92c47f0840ac2d4e1937067d050b3","observation_id":"d750f615-961d-4312-b9b0-31623bf61f2d","resolution":{"observed_at":"2026-08-07T05:32:22.677972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.692872Z","title":"Solving the job shop scheduling problem with tabu search,","venue":null,"work_id":"d82456df-c819-43f6-9f73-464aae3ffc30","year":1995},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.209572Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:b64fad6d106f2671ef18d1e5aac7f59bd1622116f116f200d96132ef09e09c61","observation_id":"50549abc-f9b5-4404-85e7-1ec750260b38","resolution":{"observed_at":"2026-08-07T05:32:22.695827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.656565Z","title":"V12. 1: User’s manual for cplex,","venue":null,"work_id":"a3a312e4-c4cf-4fa0-9891-9e17140cc815","year":2009},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.220170Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:19d16e6b4325a4d404a9936206c7937d36b718c151edbaf00228388a505ba539","observation_id":"ce1bd257-5633-4d3c-b448-b35a980e15bd","resolution":{"observed_at":"2026-08-07T05:32:22.659630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.647183Z","title":"A multi-action deep reinforcement learning framework for flexible job-shop scheduling problem,","venue":null,"work_id":"dd87eb0c-8bad-44dc-a76c-97cdb43f0a67","year":2022},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.222829Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:7c8cbd7c01a204dc3c12861b6d69a42178d5b82d643106021d6ff6265c5ec45b","observation_id":"59160295-0fcc-4c61-a0d7-d99dd56913e2","resolution":{"observed_at":"2026-08-07T05:32:22.650350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.665628Z","title":"Perron and F","venue":null,"work_id":"21a158f4-939a-4dce-87e9-be7d9d84848c","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.217605Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:7672e26b55189bb096a83d777e44fe0be3052bb77b9f03f1e8aa13d2d129cfe1","observation_id":"e80856aa-99dd-43f0-a76f-36ac61a3e681","resolution":{"observed_at":"2026-08-07T05:32:22.668690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.627948Z","title":"Residual scheduling: A new reinforcement learning approach to solving job shop scheduling problem,","venue":null,"work_id":"0daf4aa9-e0bd-4cd7-aa36-530a5a9a1f96","year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.228629Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:b9d5b2fe36a8f9bc3b83a9766e4ca981a23fef53349872a4573796dc2647b345","observation_id":"172cff2b-9b95-4d5b-91e2-603d343419cf","resolution":{"observed_at":"2026-08-07T05:32:22.631589Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.617106Z","title":"Leveraging constraint programming in a deep learning approach for dynamically solving the flexible job-shop scheduling problem,","venue":null,"work_id":"cfa4c328-2862-4dc9-8f64-9a92971e1807","year":2025},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.231286Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:a6bd99921400fa4d964e2d78792b72b27b3155a17b1d72955d2d04fd741d3737","observation_id":"81ec2c9e-c4fa-4337-97e2-d0eab33edf14","resolution":{"observed_at":"2026-08-07T05:32:22.620423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.638048Z","title":"Flexible job- PRE-PRINT SUBMITTED TO IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 21 shop scheduling via graph neural network and deep reinforcement learning,","venue":null,"work_id":"aed1fb66-1856-4568-9ca7-841969aef7cf","year":2022},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.225813Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:58094ccf5ccc6b0014469b1d8408ed1ca36cd19266e50860b757451ee3feb91f","observation_id":"c919f4fa-c0a6-4e22-a74b-c64b61acf878","resolution":{"observed_at":"2026-08-07T05:32:22.641237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.597612Z","title":"Sequence-dependent setup time flex- ible job shop scheduling problem to minimise total tardiness,","venue":null,"work_id":"3179d2bf-65f8-4119-b67b-865e40942cbb","year":2013},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.236606Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:aed717564a0ee1c55de48f6ec73d42dbd269364539a3ed9210a033b0ed9a169b","observation_id":"43022a29-9224-42f6-9538-ec364705db0a","resolution":{"observed_at":"2026-08-07T05:32:22.600840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.587556Z","title":"A simheuristic approach for the flexible job shop scheduling problem with stochastic processing times,","venue":null,"work_id":"981cf0fb-5313-4052-87aa-01b7a17986c2","year":2021},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.239562Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:f82cec6c7014fccdb2b9b2d3e3caec042588e0e5d1bb1b359203725160b6ba36","observation_id":"2979fa63-b4b9-474a-a028-f7acfe59ea62","resolution":{"observed_at":"2026-08-07T05:32:22.591039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.607547Z","title":"A constraint programming formulation of the multi-mode resource-constrained project scheduling problem for the flexible job shop scheduling problem,","venue":null,"work_id":"9b370918-f37f-496c-b4ed-cc13ccd259a0","year":2023},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.233910Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:a80a8cf3397d798416984adcee5662c43591b94dc394920990e0e707d1153827","observation_id":"ce3e6454-5837-4779-9e44-7efca8adff2a","resolution":{"observed_at":"2026-08-07T05:32:22.610903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.577544Z","title":"Gemini 2: Our most capable model yet,","venue":null,"work_id":"54de00f1-cc2a-4547-b83a-1f2f8d51a453","year":2023},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.245059Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:b80fabdd511d8701cb647abf4fadf3f4aab510d1036a932732823f03b319585c","observation_id":"90834cec-d68c-492e-9caa-a659f4d645d4","resolution":{"observed_at":"2026-08-07T05:32:22.580999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19437","last_updated":"2025-02-18T17:26:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-27T04:03:16Z","title":"DeepSeek-V3 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19437","snapshot_observed_at":"2026-08-07T05:32:22.248034Z","title":"Deepseek- v3: Scaling mixture-of-experts with multi-head latent attention,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.248034Z"},"links":{"cited_paper":"/paper/2412.19437","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:257186b4871a5258cc848f7dd59aa77f8a010ee92354ff629267cce3fce83b79","observation_id":"ef65e626-3967-44e0-80e4-26d2e2b80e14","resolution":{"observed_at":"2026-08-07T05:32:22.248034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-07T05:32:22.242189Z","title":"Gpt-4 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.242189Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:41e7e5d728add04888b897f34dc14f185ff9af87c0e029e7b890754365d8b4da","observation_id":"36910217-757e-4a35-a2f3-b0da241b4fd3","resolution":{"observed_at":"2026-08-07T05:32:22.242189Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.941958Z","title":"Available: https://arxiv.org/abs/2305","venue":null,"work_id":"9ec20556-76ba-4c6a-8acb-c34974e8f8fc","year":null},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.112949Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:f4a152abb6e3077c110562272a7b76059fac28928b5ed95d7f669351fb74699e","observation_id":"aa373b87-c828-4e34-9045-ff854e4183ca","resolution":{"observed_at":"2026-08-07T05:32:22.965259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:32:22.736327Z","title":"Available: https://arxiv.org/abs/2302","venue":null,"work_id":"51f6a3f0-eb5a-411b-85c2-70f1189755e2","year":null},"citing_paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T05:32:22.170339Z"},"links":{"citing_paper":"/paper/2506.07759"},"observation_digest":"sha256:21293cf26de5ce740ce09c63c8cb53339cabc63ef4d30975bc5c232842a86167","observation_id":"0a0c4aa9-2c92-4965-817a-408bcf2f051e","resolution":{"observed_at":"2026-08-07T05:32:22.739354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.07759","last_updated":"2025-06-09T13:38:28Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-07T05:23:50.865714Z","submitted_at":"2025-06-09T13:38:28Z","title":"REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models"},"reference_resolution":{"displayed":59,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":21,"verified_exact":4,"verified_fuzzy":33},"total_outbound_references":59},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 1 inbound Pith citation observation for arXiv:2506.07759."}